license: apache-2.0
base_model: mistralai/Ministral-3-14B-Instruct-2512
tags:
- abliteration
- uncensored
- mistral
- ministral
- 14b
language: - en
library_name: transformers
pipeline_tag: text-generation
Ministral-3-14B-abliterated
This is an abliterated (uncensored) version of Ministral-3-14B-Instruct-2512 created using the abliteration technique.
What is Abliteration?
Abliteration is a technique that removes refusal behavior from language models by identifying and modifying the internal representations responsible for refusals. This creates a model that is more willing to engage with a wider range of topics.
This model was abliterated using llm-abliteration by grimjim, which implements norm-preserving biprojected abliteration.
Further Reading
- Norm-Preserving Biprojected Abliteration - Technical deep-dive on the abliteration method
- AGI Dreams - Abliterated Models: Norm-Preserving Guardrail Removal - Overview of the abliteration technique and community discussion
Model Details
- Base Model: mistralai/Ministral-3-14B-Instruct-2512
- Parameters: ~14B
- Format: SafeTensors (BF16)
- License: Apache 2.0
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "jenerallee78/Ministral-3-14B-abliterated"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype="auto",
device_map="auto"
)
messages = [
{"role": "user", "content": "Hello, how are you?"}
]
input_ids = tokenizer.apply_chat_template(
messages,
return_tensors="pt"
).to(model.device)
outputs = model.generate(
input_ids,
max_new_tokens=512,
do_sample=True,
temperature=0.7
)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
GGUF Versions
For GGUF quantized versions compatible with llama.cpp, see: jenerallee78/Ministral-3-14B-abliterated-GGUF
Disclaimer
This model is provided for research and educational purposes. Users are responsible for ensuring their use complies with applicable laws and ethical guidelines.